Evolutionary forces are known to drive the fixation of locally adaptive genetic variation within populations, and such variation is thought to be involved in the differential response to disease and pharmacological agents observed in human populations. Natural variation is well documented in plants, and plants provide an excellent model for investigations into its genetic origins, maintenance and adaptive significance. We aim to take advantage of the natural genetic variation that occurs between populations of the genetic model plant Arabidopsis thaliana (Arabidopsis) to identify gene functions that vary between these natural populations. Such a set of polymorphic genes and gene functions will provide the essential tools required in the future to uncover the genetic mechanisms that drive the fixation of locally adaptive genetic variation within a population. To link natural genetic variation to function, we will apply our high-throughput Inductively Coupled Plasma - Mass Spectroscopy (ICP-MS) based elemental-profiling platform, in combination with powerful genetic mapping tools, to a genotyped panel of 1000 Arabidopsis accessions and Recombinant Inbred Lines (RILs). Such a system will allow the identification of loci that drive the natural variation we observe in the plant's elemental-profile or "ionome" including P, Ca, K, Mg (macronutrients);Cu, Fe, Zn, Mn, Co, Ni, Se, Mo, I (micronutrients of significance to plant and human health);Na, As, and Cd (minerals causing agricultural or environmental problems). We have demonstrated the feasibility of such studies by identifying naturally occurring alleles of several genes in Arabidopsis that function to control shoot levels of various elements, including Na, Co and Mo. Sequence analysis of the haplotypes of such loci across the large panel of Arabidopsis populations will identify which of these genes have been under recent directional selection due to local adaptation. Such information will help shed light on the evolutionary processes involved in adaptation of organisms to local environments, to understanding ion homeostasis networks and will have applications to improving the mineral content of food crops for improved human health. After all, plants provide the major source of nutrition for a large portion of the world's population.